Latest EGU highlight articles: Ocean Sciences Divisionhttps://www.egu.eu/os/publications/highlight-articles/rss/This RSS feed features highlight articles from EGU's open access
journals
"Geoscientific Model Development" and "Ocean Science".
These articles of particular interest are selected by journal editors.enTue, 03 Mar 2020 16:00:00 +0000https://cdn.egu.eu/static/29d4c63/logos/egu_claim_blue_compact.svgLatest EGU highlight articles: Ocean Sciences Divisionhttps://www.egu.eu/os/publications/highlight-articles/rss/TRAPPIST-1 Habitable Atmosphere Intercomparison (THAI):motivations and protocol version 1.0https://dx.doi.org/10.5194/gmd-13-707-2020
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<a href="https://dx.doi.org/10.5194/gmd-13-707-2020"><img src="https://cdn.egu.eu/media/filer_public_thumbnails/filer_public/d6/74/d6743648-b771-4814-bf54-23b3d486dd50/gmd.png__96x96_q90_crop_subject_location-288%2C85_subsampling-2_upscale.jpg" height="64" width="64" /></a>
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<td valign="top">Atmospheric characterization of rocky exoplanets orbiting within the habitable zone of nearby M dwarf stars is around the corner with the James Webb Space Telescope (JWST), expected to be launch in 2021.<br>
Global climate models (GCMs) are powerful tools to model exoplanet atmospheres and to predict their habitability. However, intrinsic differences between the models can lead to various predictions. This paper presents an experiment protocol to evaluate these differences.</td>
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Tue, 03 Mar 2020 16:00:00 +0000https://dx.doi.org/10.5194/gmd-13-707-2020An urban ecohydrological model to quantify the effect of vegetation on urban climate and hydrology (UT&amp;C v1.0)https://dx.doi.org/10.5194/gmd-13-335-2020
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<td valign="top">We developed a novel urban ecohydrological model (UT&amp;C v1.0) that is able to account for the effects of different plant types on the urban climate and hydrology, as well as the effects of the urban environment on plant well-being and performance. UT&amp;C performs well when compared against energy flux measurements in three cities in different climates (Singapore, Melbourne, Phoenix) and can be used to assess urban climate mitigation strategies that aim at increasing or changing urban green cover.</td>
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Thu, 06 Feb 2020 11:00:00 +0000https://dx.doi.org/10.5194/gmd-13-335-2020Why did deep convection persist over four consecutive winters (2015–2018) southeast of Cape Farewell?https://dx.doi.org/10.5194/os-16-99-2020
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<td valign="top">The region south of Cape Farewell (SCF) is recognized as a deep convection site. Convection deeper than 1300 m occurred SCF in 2015 and persisted during three additional winters. Extreme air–sea buoyancy fluxes caused the 2015 event. For the following winters, air–sea fluxes were close to the climatological average, but local cooling above 800 m and the advection below 1200 m of a fresh anomaly from the Labrador Sea decreased stratification and allowed for the persistence of deep convection.</td>
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Mon, 27 Jan 2020 11:00:00 +0000https://dx.doi.org/10.5194/os-16-99-2020Generation of Rossby waves off the Cape Verde Peninsula: the role of the coastlinehttps://dx.doi.org/10.5194/os-15-1667-2019
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<td valign="top">In December 2002 and January 2003 satellite observations of chlorophyll showed a wavelike pattern with a wavelength of about 750 km south-west of the Cape Verde Peninsula. Such a pattern suggests the existence of a locally generated Rossby wave which slowly propagated westward. To verify this hypothesis a numerical study based on a simple model has been conducted. The numerical results are completed by an analytical study which evaluates the potential impact of the coastline shape.</td>
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Mon, 30 Dec 2019 05:00:00 +0000https://dx.doi.org/10.5194/os-15-1667-2019A comparative assessment of the uncertainties of global surface ocean CO2 estimates using a machine-learning ensemble (CSIR-ML6 version 2019a) – have we hit the wall?https://dx.doi.org/10.5194/gmd-12-5113-2019
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<td valign="top">The ocean plays a vital role in mitigating climate change by taking up atmospheric carbon dioxide (CO<sub>2</sub>). Historically sparse ship-based measurements of surface ocean CO<sub>2</sub>make direct estimates of CO<sub>2</sub>exchange changes unreliable. We introduce a machine-learning ensemble approach to fill these observational gaps. Our method performs incrementally better relative to past methods, leading to our hypothesis that we are perhaps reaching the limitation of machine-learning algorithms’ capability.</td>
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Tue, 17 Dec 2019 05:00:00 +0000https://dx.doi.org/10.5194/gmd-12-5113-2019The biophysics, ecology, and biogeochemistry of functionally diverse, vertically and horizontally heterogeneous ecosystems: the Ecosystem Demography model, version 2.2 – Part 1: Model descriptionhttps://dx.doi.org/10.5194/gmd-12-4309-2019
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<td valign="top">Our paper describes the Ecosystem Demography model. This computer program calculates how plants and ground exchange heat, water, and carbon with the air, and how plants grow, reproduce and die in different climates. Most models simplify forests to an average big tree. We consider that tall, deep-rooted trees get more light and water than small plants, and that some plants can with shade and drought. This diversity helps us to better explain how plants live and interact with the atmosphere.</td>
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Fri, 08 Nov 2019 14:49:44 +0000https://dx.doi.org/10.5194/gmd-12-4309-2019The biophysics, ecology, and biogeochemistry of functionally diverse, vertically and horizontally heterogeneous ecosystems: the Ecosystem Demography model, version 2.2 – Part 2: Model evaluation for tropical South Americahttps://dx.doi.org/10.5194/gmd-12-4347-2019
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<td valign="top">The Ecosystem Demography model calculates the fluxes of heat, water, and carbon between plants and ground and the air, and the life cycle of plants in different climates. To test if our calculations were reasonable, we compared our results with field and satellite measurements. Our model predicts well the extent of the Amazon forest, how much light forests absorb, and how much water forests release to the air. However, it must improve the tree growth rates and how fast dead plants decompose.</td>
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Tue, 29 Oct 2019 13:06:05 +0000https://dx.doi.org/10.5194/gmd-12-4347-2019Improved methodologies for Earth system modelling of atmospheric soluble iron and observation comparisons using the Mechanism of Intermediate complexity for Modelling Iron (MIMI v1.0)https://dx.doi.org/10.5194/gmd-12-3835-2019
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<td valign="top">MIMI v1.0 was designed for use within Earth system models to simulate the 3-D emission, atmospheric processing, and deposition of iron and its soluble fraction. Understanding the iron cycle is important due to its role as an essential micronutrient for ocean phytoplankton; its supply limits primary productivity in many of the world’s oceans. Human activity has perturbed the iron cycle, and MIMI is capable of diagnosing many of these impacts; hence, it is important for future climate studies.</td>
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Mon, 02 Sep 2019 00:00:00 +0000https://dx.doi.org/10.5194/gmd-12-3835-2019CO2 effects on diatoms: a synthesis of more than a decade of ocean acidification experiments with natural communitieshttps://dx.doi.org/10.5194/os-15-1159-2019
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<td valign="top">Diatoms are a group of phytoplankton species responsible for ~ 25% of primary production on Earth. Ocean acidification (OA) could influence diatoms but the key question is if they become more or less important within marine food webs. We synthesize OA experiments with natural communities and found that diatoms are more likely to be positively than negatively affected by high CO<sup>2</sup> and larger species may profit in particular. This has important implications for ecosystem services diatoms provide.</td>
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Wed, 28 Aug 2019 00:00:00 +0000https://dx.doi.org/10.5194/os-15-1159-2019High-resolution underwater laser spectrometer sensing provides new insights into methane distribution at an Arctic seepage sitehttps://dx.doi.org/10.5194/os-15-1055-2019
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<td valign="top">Methane seepage from the seafloor west of Svalbard was investigated with a fast-response membrane inlet laser spectrometer. The acquired data were in good agreement with traditional sparse discrete water sampling, subsequent gas chromatography, and with a new 2-D model based on echo-sounder data. However, the acquired high-resolution data revealed unprecedented details of the methane distribution, which highlights the need for high-resolution measurements for future climate studies.</td>
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Tue, 13 Aug 2019 00:00:00 +0000https://dx.doi.org/10.5194/os-15-1055-2019